when heirs become major shareholders 20140606 - uni … · 2019. 9. 29. · munich personal repec...

Munich Personal RePEc Archive

When Heirs Become Major Shareholders:

Evidence on Tunneling and Succession

through Related-Party Transactions

Hwang, Sunwoo and Kim, Woochan

February 2014

Online at https://mpra.ub.uni-muenchen.de/56487/

MPRA Paper No. 56487, posted 12 Jun 2014 18:14 UTC

- 1 -

When Heirs Become Major Shareholders*

Evidence on Tunneling and Succession through Related-Party Transactions

Sunwoo Hwang† and Woochan Kim

‡

This Draft: February, 2014

Abstract

In family firms, the succession of controlling equity stake to next generation is an issue of paramount

importance. This, however, can be a major challenge in the presence of heavy inheritance or gift tax

burden (high tax rate and absence of tax-saving vehicles, such as trusts or foundations) and in the absence

of dual-class equity. Such regulatory environment may lead families to seek alternative ways of succession.

As for families controlling business groups, one way of doing so is making use of related-party

transactions among member firms. By favoring firms where the heir holds significant equity stake, the

family can tunnel corporate resources to the heir. Eventually, the firm can grow large enough to acquire

controlling equity stakes in other firms within the group. In this paper, we investigate this possibility using

Korean chaebol firms during a sample period of 2000-2009. We identify firms where heirs become a

major shareholder (treatment group) and compare them against their year-industry-size-matched firms

(control group) before and after the ownership change. Difference-in-differences test with firm fixed

effects reveal that treatment group firms experience greater related-party transactions, benefit from them

in terms of earnings, pay out more dividends, and become more important in controlling other firms in the

group.

JEL classification: G30, G32, G34

Keywords: family firm, business group, chaebol, succession, related-party transactions, control-enhancement

* We thank workshop participants at Korea University Business School, Seoul National University

Business School, and Sungkyunkwan University Business School for their comments. We also thank KDI

School of Public Policy and Management and Asian Institute of Corporate Governance (AICG) for

financial support. † Kenan-Flagler Business School, The University of North Carolina at Chapel Hill, McColl Building,

Chapel Hill, NC 27599, USA, E-mail: [email protected] ‡ Corresponding author; Associate Professor of Finance, Korea University Business School, Anam-Dong,

Seongbuk-Gu, Seoul 136-701, Republic of Korea, E-mail: [email protected]

- 2 -

1. Introduction

In family firms, the succession of controlling equity stake to next generation is an issue of

paramount importance. A successful succession allows the family to perverse its control for

another generation. Depending upon who succeeds the equity stake, it will also greatly influence

the decision on who will be the next CEO. One can say that ‘managerial’ succession is of

secondary importance compared to ‘ownership’ succession.

In the existing finance literature, there is a growing body of research on family firm

performance (McConaughy et al., 1998; Anderson and Reeb, 2003; Maury, 2006; Villalonga and

Amit, 2006; Miller et al., 2007; Andres, 2008), the management succession of family firms

(Smith and Amoako-Adu, 1999; Bennedson et al., 2007; Cucculelli and Micucci, 2008) and the

control-enhancing mechanisms family firms use (La Porta, López de Silanes, and Shleifer, 1999;

Claessens, Djankov, and Lang, 2000; Nenova, 2001; Faccio and Lang, 2000; Villalonga and Amit,

2009; Gompers, Ishii, and Metrick, 2010). But surprisingly, no paper exists on the succession of

family ownership. This paper aims to make a small step in filling this gap .

Handing over controlling equity stake from one generation to another generally faces two

challenges. One is the risk of dilution and the other is the risk of taxation. If a family firm

repeatedly relies on external equity financing, the equity stake later generations inherit may not

be large enough to warrant control over the firm. In certain jurisdictions, this challenge is

resolved with the use of dual-class equity or voting agreements (Villalonga and Amit, 2009).

Descendants that hold shares with multiple voting rights or that entered contract with

shareholders ceding their voting power can be free from the risk of dilution.

The risk of taxation is another major challenge. Although some jurisdictions have abolished

inheritance tax, many still retain it.1 In the U.S. the tax rate is as high as 35%. Also, even if

abolished, capital gains tax may still apply upon the transfer of wealth. Gift tax also has been

abolished in recent years, and even if it exists, many deductions and exemptions apply.

Nevertheless, there are nontrivial number of jurisdictions that still retain it. In certain

jurisdictions, this challenge of taxation is resolved with the use of trusts or private foundations

1 Some jurisdictions use the term estate tax instead of inheritance tax.

- 3 -

that receive shares as donation (Villalonga and Amit, 2009). As charitable entities, they are

exempt from taxation, but still governed by family members who serve as trustees or board of

directors.

What if dual-class equity is prohibited by law, voting agreement counterparties are hard to

find, and trusts or private foundations are heavily regulated? Founding family would have a

strong incentive to seek alternative ways of handing over controlling equity stake to their

descendants. One alternative is forming a business group and letting the heir own a controlling

equity stake in a firm or multiple firms that control others. The business group can have a

pyramidal structure, but this is not necessary. Cross- or circular-shareholdings can also serve the

same purpose. But, there is a critical problem with this scheme. The heir may not have enough

wealth in the beginning to acquire controlling equity stake in the firm that controls others.

There are two possible solutions to this. One is making the holding company or the de facto

holding company (in case the group does not have a pyramidal structure) issue new shares

privately to the heir at a heavily discounted price, so that the heir can acquire controlling equity

stake in the holding company with low financial burden.2 This, however, is not possible for

publicly-traded companies, where preemptive rights of existing shareholders are typically well

protected. Even for privately-traded ones, tax implications will prevent the use of such scheme.

An alternative solution is tunneling corporate wealth from one firm to another through

related-party transactions. That is, setting up a privately-traded firm, where the heir is a major

shareholder, and instructing other firms to purchase goods and services from that firm. Increased

sales and earnings of this firm will increase its asset size. Eventually, the firm can grow large

enough to acquire controlling equity stakes in other firms within the group. The firm may also

pay out dividends so that the heir can directly acquire shares in other firms. Thus, family

ownership can be in the hands of the heir without paying any gift or inheritance tax to the

government.

This possibility implies that any serious research on the succession of family ownership must

also consider changes in intra-group ownership structure and related-party transactions among

2 Same purpose can be served with a convertible bond or a bond with warrant with heavily discounted

conversion ratio or exercise price.

- 4 -

member firms. In this paper, we attempt to do this by studying a country – Korea – that perfectly

matches the setting we initially considered. That is, a country where dual-class equity is

prohibited by law, voting agreement counterparties are hard to find, and trusts or private

foundations are heavily regulated.

Anecdotal evidence of family ownership succession through tunneling abounds among

Korean chaebols – family-controlled business groups in Korea. An exemplary case is Hanwha

S&C, an integrated IT service firm of Hanwha group (also see Figure 1). Originally, it was

wholly owned by Kim Seung-youn (33.3%), the group chairman of Hanwha group, and Hanwha

Corp (67.7%). But, by 2007, the shares of Hanwha S&C was sold to the chairman’s three sons,

each owning 50%, 25%, and 25%.3 Since then, Hanwha S&C’s sales to member firms soared

from 117 billion Korean won (approximately, 117 million US dollars) in 2007 to 319 billion

Korean won in 2010. Its earnings (EBIT) also jumped from 11 billion Korean won in 2007 to 24

billion Korean won in 2010. This improved financial strength enabled Hanwha S&C to acquire

shares in other member firms. As of 2012, it holds shares of Hancomm (70%), Hanwha

Corporation (2.2%), Hanwha Total Energy (100%), Hanwha General Insurance (0.37%), Yeosu

Cogeneration System (100%), Hanwha Solar Energy (20%), and Human Power (100%). Prior to

2007, Hancomm was the only firm, in which Hanwha S&C held shares.

To test our predictions using Korean chaebols during the sample period of 2000-2009, we

identify firms where heirs become a major shareholder (treatment group) and compare them

against their year-industry-size-matched firms (control group) before and after the ownership

change. Difference-in-differences test with firm fixed effects reveal a number of results consistent

with our predictions. First, related-party transactions increase in treatment group firms after the

3 In May 2010, the shareholders of Hanwha Corp. filed a derivative suit against the directors of Hanwha

Corp. for selling Hanwha S&C shares below the DCF value. In this civil charge, the shareholders asked

for a compensation of 45 billion Korean won (approximately, 45 million US dollars). In October 2013,

Seoul Central District Court ordered the directors to pay back to the company 8.9 billion Korean won,

which is well below the originally estimated damage. At the time of this writing, the case is at the

appellate court. In a separate criminal case (embezzlement), Chairman Kim was sentenced a three-year

prison with a five-year suspension (finalized in February 2014). But, he was acquitted from the charge of

selling Hanwha S&C shares below the DCF value. These results indicate how difficult it is to prevent

tunneling with ex post legal remedies.

- 5 -

treatment. Second, earnings increase with related-party transactions in treatment group firms after

the treatment. Third, dividend payout increase with related-party transactions in treatment group

firms after the treatment. Fourth, importance in group control increases with related-party

transactions in treatment group firms after the treatment. We measure the importance in group

control by marginal contribution to group control used in Kim, Lim, and Sung (2007). Further

analyses reveal that our results are driven by related-party sales to member firms rather than

related-party purchases from them.

We also conduct a number of falsification tests. First, we run similar difference-in-differences

regressions using treatment group firms where ‘non-heirs’ become a major shareholder. We do

not find any increase in related-party transactions in these firms after the treatment. Second, we

run similar difference-in-differences regressions where counterparties of the original treatment

group firms (e.g., firms where heir become a major shareholder) are used as our new treatment

group. Again, we do not find any increase in earnings, dividend payouts, or control over other

firms in these new treatment group firms after the treatment.

Our paper contributes to the existing literature in three ways. First, to the best of our

knowledge, this is the first paper on ‘family ownership’ succession, which we believe is an issue

of paramount importance in family firms, but its research virtually missing in the existing finance

literature. As mentioned earlier, the main focus of existing literature is on ‘managerial’ succession.

Second, we contribute to family firm performance studies, which became popular since

Anderson and Reeb (2003). We contribute to this area of study by highlighting the importance of

related-party transactions when assessing performance, especially when family firms are parts of

a business group. More remotely, our study is also related to the studies on managerial ownership

and firm performance (Morck, Shleifer, and Vishny, 1988). Again, in a business group setting, the

relationship between ownership and performance cannot be assessed without considering related-

party transactions.

Third, we add to the literature on business group tunneling (Bae, Kang, and Kim, 2002;

Bertrand, Mehta, and Mullainathan, 2002; Cheung, Rau, and Stouraitis, 2006; Baek, Kang, and

Lee, 2006). We report empirical evidence that related-party transactions between member firms

can be used as a tunneling vehicle benefiting founding family members at the expense of outside

- 6 -

minority shareholders. Our evidence on tunneling, however, is indirect in nature like in any other

tunneling papers.

This paper is organized as follows. Section 2 and 3 explain our research design, data, and key

variables. Section 4 reports our empirical results, and Section 5 concludes.

2. Research Design

In this paper, our aim is to quantify the effect of ownership change on firm’s related-party

transactions, earnings, dividend payouts, and its control over other firms. An obvious challenge to

this is the endogeneity of ownership change. To address this, difference-in-differences (DiD) or

instrumental variable (IV) approach making use of an exogenous shock to ownership change is in

order. But, unfortunately, we do not have such a shock in our sample – Korean chaebol firms

during 2000-2009.

So, we take a second-best approach of using covariate-matched control group firms. First, we

identify firm-years that experienced a major increase in heir’s ownership. We label this set of

firms as the treatment group. Second, for each treatment group firm, we identify its match among

firms that did not experience any major change in family ownership during our sample period and

that is from another chaebol group.4 We use three matching covariates: year, industry, and firm’s

asset size. Given the dominance of manufacturing firms in Korea, we use 4-digit Korea SIC code

for manufacturing and 2-digit for others. We label this set of firms as the control group, and

expect that the use of matching firms will significantly lower the risk of self-selection bias. Third,

by conducting difference-in-differences test, we compare these two groups of firms before and

after the treatment.

More specifically, we run the following regression to verify whether treatment group firms

experience greater increase in related-party transactions than control group firms after the

treatment.

4 Major family ownership changes include changes in heir’s net ownership by more than 5%p, changes in

controlling shareholder’s net ownership by more than 5%p, and changes in other relatives’ net ownership

by more than 5%p.

- 7 -

ittiitiitiit XTPTGTPTGRPT ενµβββα +++Φ+⋅+++= 210 (1)

itRPT is related-party transactions of firm i with other member firms at year t . We explain the

details of its measurement in the next section. iTG is a treatment group dummy that takes a value

of 1 if firm i is treated (experience a major increase in heir’s ownership during 2000-2009) and 0

otherwise. We explain what we exactly mean by ‘a major increase in heir’s ownership’ in the next

section. itTP is a treatment period dummy that takes a value of 1 if firm i is treated at year t or

before. Notice that this treatment period dummy is defined separately for each treatment group

firm i . Firm i and firm i ’s matching firm takes the same value for itTP . X is a column vector of

control variables. iµ and tν are respectively firm- and year-fixed effects. The coefficient of interest

is 2β , which we expect to be positive and statistically significant. Since same firms appear

multiple times in this panel regression, we use coefficient standard errors clustered at the firm-

level. Control variables include firm size, firm age, leverage, and a number of time-varying

dummies intended to capture abrupt changes in the volume of related-party transactions (spin-

offs, mergers, and new group affiliations). See Table 2, Panel A for their definitions.

To see whether the tendency of earnings increasing with related-party transactions strengthen

in treatment group firms after the treatment, we run the following regression with triple

interactions.

ittiititi

itititiitiititiit

XRPTTPTG

RPTTPRPTTGTPTGRPTTPTGEBITDA

ενµβ

ββββββα

+++Φ+⋅⋅+

⋅+⋅+⋅++++=

6

543210 (2)

itEBITDA is earnings before interest, tax, depreciation, and amortization of firm i at year t . We

explain the details of its measurement in the next section. Other variables are defined earlier. The

coefficient of interest is 6β , which we expect to be positive and statistically significant. Control

variables include firm size, firm age, leverage, cash holdings, R&D expenditure, and advertising

expenditure.

- 8 -

To see whether the tendency of dividend payout increasing with related-party transactions

strengthen in treatment group firms after the treatment, we run the following regression with

triple interactions.

ittiititi

itititiitiititiit

XRPTTPTG

RPTTPRPTTGTPTGRPTTPTGDIV

ενµβ

ββββββα

+++Φ+⋅⋅+

⋅+⋅+⋅++++=

6

543210 (3)

itDIV is cash dividend (including dividends paid out to preferred shareholders) paid out by firm i

at year t . We explain the details of its measurement in the next section. Other variables are

defined earlier. The coefficient of interest is 6β , which we expect to be positive and statistically

significant. Control variables include firm size, firm age, and leverage.

To see whether control over other member firm’s sensitivity to related-party transactions

strengthen in treatment group firms after the treatment, we run the following regression with

triple interactions.

ittiititi

itititiitiititiit

XRPTTPTG

RPTTPRPTTGTPTGRPTTPTGMCI

ενµβ

ββββββα

+++Φ+⋅⋅+

⋅+⋅+⋅++++=

6

543210 (4)

itMCI is marginal contribution to group control index of firm i at year t . We explain the details of

its measurement in the next section.

We conduct two falsification tests in this paper. First, we run difference-in-differences

regression (1) using treatment group firms where ‘non-heirs’ become a major shareholder. In this

regression, iTG takes a value of 1 if firm i experiences a major increase in non-heir’s ownership

during 2000-2009 and 0 otherwise. If the increase in related-party transactions are for the benefit

of heirs and their successions, they should not respond to changes in ‘non-heir’s’ ownership.

Second, we run difference-in-differences regressions (2) - (4), where counterparties of the

original treatment group firms (e.g. firms where heir becomes a major shareholder) are used as

our new treatment group. Again, if the increase in related-party transactions are for the benefit of

heirs and their successions, one should not see firms in the other side of transaction producing

- 9 -

higher earnings, paying out more dividends, or strengthening control over other firms.

3. Data and Key Variables

A. Sample Chaebol Groups

Our treatment and control group firms are from 26 chaebol groups that have been designated as

large business group by Korea Fair Trade Commission (KFTC) for at least 6 years during our

sample period of 2000-2009 (e.g. designated in the Aprils of 2001 to 2010). Table 1 lists the name

of 26 chaebol groups and the number of their member firms in each year. Since 1987, KFTC has

been designating large business groups and their member firms every year in April. Designation

depends on the aggregate size of member firms’ assets (net asset in case of financial firms),

measured at the end of prior year December. During 1993-2002, KFTC designated 30 largest

business groups without using any size threshold. During 2002-2008, KFTC used an explicit

threshold of 2 trillion Korean won and designated any group above the threshold as a large

business group. Since 2009, KFTC is using the threshold of 5 trillion won.

When announcing the list of large business groups, KFTC also announces the person who

controls the group and the list of firms under its control. For us, this is a very convenient feature

since we do not need to come up with an algorithm of our own to identify them. Control is

explicitly defined in the Monopoly Regulation and Fair Trade Act and its enforcement decree. It

considers not only shares directly owned, but also those indirectly owned through related parties,

such as relatives and other member firms. It also considers channels of influence that do not rely

on share ownership. A person in control can be both, a natural person or a legal person. In this

paper, we exclude the latter and focus on the former. For details on the identification of member

firms and the person in control, see Kim, Lim, and Sung (2007).

B. Major Increase in Heir’s Ownership

Since 2007, KFTC made public the detailed ownership structure of large business groups it

designates. This is done through a portal site, named OPNI, from which we download all the

necessary data for this paper. The data is available from 2000. When it comes to share ownership

- 10 -

among member firms, this data gives a complete picture. Complicated web of intragroup

ownership structure is summarized in a simple nn × matrix, where n is the number of member

firms. In this matrix, element ijx is the fraction of shares firm j owns in firm i .

But, when it comes to share ownership by controlling person’s family members, the data is

incomplete in a sense that it does not give information for each individual family member. For

privacy reasons, family owned shares are broken down into three groups: shares held by the

controlling shareholder (the person in control of the group), the immediate family members, and

the other relatives. Immediate family members include the spouse, the parents, and the children.

Other relatives include those within certain degrees of kinship (six with the controlling

shareholder or four with the spouse).

In this paper, we regard the shares held by immediate family members as those held by the

heir. There can be two potential problems for doing so. One is that it includes the shares held by

spouse and parents. Another has to do with the possibility of younger siblings, instead of children,

succeeding family ownership. The first problem is trivial since spouse and parents hardly own

shares.5 Among the treatment group firms we study in this paper, there is only one firm with

spouse’s ownership and none with parents’. In our robustness check, we obtain virtually the same

result after excluding this firm from the sample.6

The second problem is not a concern either since there are only a limited number of cases

where the group chairman position is succeeded by a younger sibling. A good example is Doosan,

where five brothers have taken turns in assuming the position. But, even in this case, shares have

not changed hands between brothers. Each brother inherited shares from their parents, and they

too are giving their shares to their respective children.

Our treatment group dummy iTG takes a value of 1 if firm i experiences a major increase in

heir’s ownership during 2000-2009 and 0 otherwise. A ‘major increase in heir’s ownership’

5 According to Economic Reform Research Institute (ERRI, 2012) the average (median) fraction of

spouse’s ownership out of that of immediate family is only 5.7% (0.1%) as of 2011 in case of top 20

chaebol groups. 6 Since 2009, each individual family member is required to disclose their detailed share ownership in each

member firm. In this paper, however, we do not make use of this data. At the time of this writing, this data

covers only four years, which is too short to investigate the key hypotheses of this paper.

- 11 -

means that its ‘net’ ownership (heir’s ownership – controlling shareholder’s ownership – other

relatives’ ownership) increases by more than 5%p and that its ownership is greater than those of

controlling shareholder’s and other relatives’. That is, HNOWN _Δ > p%5 , HOWN _ >

COWN _ , and HOWN _ > ROWN _ , where HNOWN _Δ is change in heir’s net ownership, and

HOWN _ , COWN _ , ROWN _ are respectively the ownership held by the heir, the controlling

shareholder, and other relatives.

Two points are worth noting here. First, we focus on ownership relative to other family

members (e.g. net ownership). If ownership increases not only for the heir, but also for others, the

subsequent increase in related-party transactions cannot be regarded as those just for the heir.

Likewise, the subsequent increase in firm’s importance in group control cannot be regarded as

that for the heir’s succession. By focusing on net ownership, we can effectively rule out such

alternative explanations. But, we do not exclude the possibility where the ownership of heir and

others both drop, but the drop of others is greater.7 Second, we impose a condition that the heir is

the largest shareholder among the family members. So, we exclude cases where heir’s net

ownership increases by more than 5%p, but its ownership is yet below that of other family groups.

Other treatment group dummies used in our falsification tests are similarly defined.

C. Marginal Contribution to Group Control

itMCI is the marginal contribution to group control index of firm i at year t . This index, originally

from Kim, Lim, and Sung (2007), is a measure devised to identify firms, through which a

controlling shareholder can most efficiently strengthen his control over other firms in the same

group. To be an efficient control vehicle, this firm must hold equity stakes in other firms, which

in turn hold equity stakes in others, which in turn hold equity stakes in others, and so on. One

way to quantify the degree of such direct and indirect equity holdings is to compute the cash flow

rights a controlling shareholder can additionally obtain from other firms when the vehicle firm

becomes a part of the group. Alternatively, one can compute the cash flow rights a controlling

shareholder will have to lose from others when the vehicle firm is no longer a group firm. By

7 Three such cases exist in our sample. If we drop them, statistical significance weakens, but our basic

results remain intact.

- 12 -

scaling this additional cash flow rights by the vehicle firm’s book equity, one can have a measure

that captures marginal contribution to group control. That is, the additional dollar amount of

equity one can obtain in other firms by investing one dollar of equity in the vehicle firm. Notice

that this measure does not identify firms that currently has the largest equity stakes in other firms.

Rather, it identifies firms that will become one in the future. The controlling shareholder that

wishes to maximize his control for a given amount of equity investment, has the incentive to

enlarge the firm with the highest MCI and let it grow into a firm that has the largest equity stakes

in other firms. Equation (4) shows the formula of firm i ’s marginal contribution to group control

index:

it

n

ijj

n

ijj

i

jtjtjtjt

itBE

cfrBEcfrBE

MCI

≠= ≠=

−−

=,1 ,1

(4)

itBE is firm i ’s book value of equity at year t . jtcfr is the cash flow rights controlling family has

in firm j when all member firms are included in the group. i

jtcfr−

is cash flow rights controlling

family has in firm j when all member firms, but firm i , are included in the group. The first term in

the numerator measures total cash flow rights the controlling family would receive from other

firms (denoted as j ) when firm i ( ji ≠ ) is included in the group. The second term in the

numerator captures total cash flow rights the control family would receive from other firms

(denoted as j ) when firm i ( ji ≠ ) is excluded from the group. We divide the difference by the

firm’s book equity to control for any size effect, since larger firms are more likely to have greater

contributions to group control.8

8 Our measure is similar, but not identical to the ‘centrality’ measure introduced by Almeida et al. (2011).

They identify firms by computing the average decrease in critical control threshold (CC) across all group

firms other than firm i, after excluding firm i from the group. Critical control (CC) threshold is the highest

control threshold that is consistent with family control of a firm. Control threshold T is the minimum votes

a family needs to hold directly or indirectly to control a firm. This measure has an advantage of using

voting rights, which we wish to capture, instead of cash flow rights. But, this measure is not adjusted for

firm size, and therefore has a tendency of favoring large firms that already has large control over others.

- 13 -

The index can have a value equal to zero. This happens when firm i does not have any equity

investment in other member firms. It should also be noted that the index has no upper bound. If

there is no restriction on debt or the length equity investment chain, the index can be well above

‘1.’ So, we winsorize the index at its 99th

percentile value.

Cash flow rights ( jtcfr ) is the sum of controlling family’s direct and indirect ownership.

Again, we follow Kim, Lim, and Sung (2007) and compute cash flow rights as follows:

⋅⋅⋅+++= = = =

n

k

n

k

n

l

lkljkkjkjjt dssdsdcfr1 1 1

(5)

jd is controlling family’s direct ownership in firm j at year t . Family includes the controlling

shareholder, its spouse, and relatives within certain degrees of kinship (six with the controlling

shareholder or four with the spouse). The subsequent terms are indirect ownership through

member firms under the control of the same controlling shareholder. For example, the second

term is family’s indirect ownership in firm j through firm k ( k can take values from 1 to n ). The

third term is family’s indirect ownership in firm j through firm k and firm l ( l can also take values

from 1 to n ). Since we know the intragroup ownership structure in a matrix form ( S ), a vector of

cash flow rights ( cfr ) can be easily computed by the following formula, where d is the vector of

direct family ownership.

( ) dSIcfr 1−−= (6)

D. Others

itRPT is the natural logarithm of 1 plus the sum of firm i ’s related-party sales to member firms at

year t plus firm i ’s related-party purchases from member firms at year t . Sales and purchases are

measured in million Korean won (approximately thousand US dollars) and adjusted for inflation

using Bank of Korea’s GDP deflator (base year = 2005). itRPS is the natural logarithm of 1 plus

the firm i ’s related-party sales to member firms at year t . itRPP is the natural logarithm of 1 plus

the firm i ’s related-party purchases from member firms at year t .

- 14 -

itEBITDA is the signed natural logarithm of earnings before interest, tax, depreciation, and

amortization of firm i at year t . A signed logarithm takes the logarithm of the absolute value of the

variable and assigns the original sign. Values for absolute value less than one are set to be zero.

Since we have many privately-traded firms in our sample, we use EBITDA instead of Tobin’s q

as our measure of firm performance. As is the case with related-party transactions, EBITDA is

also in million Korean won and adjusted for inflation using Bank of Korea’s GDP deflator (base

year = 2005). itDIV is the natural logarithm of 1 plus the cash dividend (including dividends paid

out to preferred shareholders) paid out to firm i at year t . Dividends are measured in million

Korean won and adjusted for inflation using Bank of Korea’s GDP deflator (base year = 2005).

Notice that we deliberately do not scale related-party transactions (RPT) or earnings by sales.

The focus of this paper is not on the fraction of RPT over sales nor on profit margins. Rather, we

are interested in the increase in earnings volume thanks to increase RPTs. Larger earnings matter

because it helps the firm to hold more equity stakes in other firms or payout more dividends to

the heir. But, we do control for size in our regressions. We include firm’s total assets in natural

logarithm as a covariate in our regressions. Total assets are also in million Korean won and

adjusted for inflation using Bank of Korea’s GDP deflator (base year = 2005).

The data on related-party transactions are available originally from each company’s business

reports (similar to 10K in US), but can be massively downloaded from KIS-Value, a financial

database administered by NICE Credit Information Service Co., Ltd. KIS-Value provides RPT

data not only for publicly-traded listed firms, but also for externally-audited private firms.

TS2000, a financial database administered by the Korea Listed Companies Association (KLCA),

provides RPT data limited to publicly-traded listed firms, but it gives the breakdown of RPT data

for each counterparty firm. itE and all other accounting variables used as controls are from

TS2000.

4. Results

A. A Preliminary Look

- 15 -

Table 2 gives the definition (Panel A) and the summary statistics (Panel B) of variables used in

this paper. Table 3 shows how changes in related-party transactions, earnings, and dividends vary

with changes in net ownership. It reports median (Pane A) and mean (Panel B) of paired-sample

differences in related-party transactions (RPTit, RPSit, RPPit), earnings (EBITDAit), and dividend

payouts (DIVit) before and after net ownership change of various degrees (±5%p, ±10%p, and

±15%p) for each family group (heir, controlling shareholder, and other relatives). The last three

columns report the average number of years before and after the net ownership change and the

number of firms used in the calculation for each level of ownership changes.

A number of observations can be made. First, the changes in related-party transactions and

earnings are positive, regardless of the level of net ownership change and the family member

being investigated. This is so even when they are all adjusted for inflation. Second, there is a

clear tendency of related-party transactions (RPTit, RPSit, RPPit) and earnings (EBITDAit)

increasing to a greater extent for larger changes in heir’s net ownership. Median changes in RPTit,

RPSit, RPPit, and EBITDAit respectively jump from 0.32, 0.16, 0.09, and 0.3 to 1.38, 1.13, 1.67,

and 1.11 as we move from the net ownership change of 15%p. The mean changes

look even more pronounced. Third, we can find a similar pattern for the controlling shareholder.

Median changes in RPTit, RPSit, RPPit, EBITDAit, and DIVit respectively jump from 0.59, 0.35,

0.59, 0.29, and 0.11 to 0.92, 0.58, 2.70, 0.55, and 0.36 as we move from the net ownership

change of 15%p. The jump, however, is much moderate than that for the heir with the

exception of related-party purchases. Similar pattern emerges when using ‘mean’ changes rather

than ‘median’ changes. Fourth, the patterns for other relatives are mixed. When using median

changes, there is a tendency of RPTit, RPSit, RPPit, EBITDAit, and DIVit increasing as we move

from the net ownership change of 15%p. But, such patter disappears when using mean

changes. Fifth, the changes in related-party transactions or earnings do not fall as we move from

the net ownership change of

- 16 -

Table 4 reports our first difference-in-differences (DiD) regression results. They are firm fixed

effects regressions of related-party transactions (RPTit, RPSit, and RPPit) on treatment group

dummy (TGi), treatment period dummy (TPit), their interaction (TGi x TPit), control variables,

and year dummies. We also include time-varying dummies capturing spin-offs, mergers, and new

affiliates, but their coefficients are suppressed. Treatment group dummy (TGi) is absorbed in firm

FE. Sample includes 36 treatment group firms that experienced major increase in heir’s

ownership and 36 control group firms identified by covariate matching based on year, industry

(4-digit code for manufacturing and 2-digit code for others), and asset size. t-values are reported

in the parenthesis, and are based on standard errors clustered at the firm level.

The coefficients of our interest (the coefficients on TGi x TPit) are all positive and marginally

significant. The coefficients of -0.2667 on TPit and 0.6021 on TGi x TPit in column (2) imply that

a firm experiencing a major increase in heir’s ownership also experiences a jump in related-party

sales by 0.3354 (=0.6021 – 0.2667), while its matching firm experiences a drop in related-party

sales by 0.2667. The difference-in-differences 0.6021 is approximately 6% of RPSit’s median

value (10.4). Among the controls, firm size is most significant.

C. Ownership Change, Related-Party Transactions, and Earnings

Table 5 reports our second difference-in-differences (DiD) regression results. They are firm fixed

effects regressions of earnings (EBITDAit) on treatment group dummy (TGi), treatment period

dummy (TPit), related-party transactions (RPTit, RPSit, or RPPit), their interactions, control

variables, and year dummies. Treatment group dummy (TGi) is absorbed in firm FE. Again,

sample includes 36 treatment group firms that experienced major increase in heir’s net ownership

and 36 control group firms identified by covariate matching based on year, industry (4-digit code

for manufacturing and 2-digit code for others), and asset size. t-values are reported in the

parenthesis, and are based on standard errors clustered at the firm level.

The coefficients of our interest (the coefficients on TGi x TPit x RPTit) are positive and

statistically significant when using related-party sales (column 2), positive and marginally

significant when using related-party transactions (sum of related-party sales and purchases), but

not significant when using related-party purchases (column 3). These results indicate that, it is

- 17 -

related-party sales, not related-party purchases, that benefit the treatment group firms after the

treatment. Purchasing raw materials and intermediate goods in favorable terms from other

member firms can be a source of profit. But, we do not see this effect in our sample. Rather, we

see firms benefiting greatly from sales of goods and services to other member firms.

This is consistent with the accusations made by non-governmental organizations (NGO) and

popular press against Korean chaebols.9 According to the reports they published, heirs benefit

from their equity stakes in firms that heavily rely on related-party sales to member firms. These

firms are mostly found in IT services, logistics, advertising, and constructions.

D. Ownership Change, Related-Party Transactions, and Dividend Payouts

Table 6 reports our third difference-in-differences (DiD) regression results. They are firm fixed

effects regressions of dividend payouts (DIVit) on treatment group dummy (TGi), treatment period

dummy (TPit), related-party transactions (RPTit, RPSit, or RPPit), their interactions, control

variables, and year dummies. Treatment group dummy (TGi) is absorbed in firm FE. Again,

sample includes 36 treatment group firms that experienced major increase in heir’s net ownership

and 36 control group firms identified by covariate matching based on year, industry (4-digit code

for manufacturing and 2-digit code for others), and asset size. t-values are reported in the

parenthesis, and are based on standard errors clustered at the firm level.


marginally significant when using related-party sales (column 2), but not significant when using

related-party transactions (column 1) or related-party purchases (column 3). These results

indicate that, it is related-party sales, not related-party purchases, that benefit the treatment group

firms after the treatment, and allow them to pay out more dividends. Again, this is consistent with

the accusations made by non-governmental organizations (NGO) and popular press that heirs

benefit from their equity stakes in firms that heavily rely on related-party sales to member firms.

E. Ownership Change, Related-Party Transactions, and Group Control

9 Solidarity for Economic Reform (SER) and its sister organization, Economic Reform Research Institute

(ERRI), are the two pioneering NGOs in this area. Since 2006, they have been publishing a number of

reports on related-party sales aimed to benefit controlling family members.

- 18 -

Table 7 reports our fourth difference-in-differences (DiD) regression results. They are firm fixed

effects regressions of marginal contribution to group control index (MCIit) on treatment group

dummy (TGi), treatment period dummy (TPit), related-party transactions (RPTit, RPSit, or RPPit),

their interactions, and year dummies. Treatment group dummy (TGi) is absorbed in firm FE.

Again, sample includes 36 treatment group firms that experienced major increase in heir’s net

ownership and 36 control group firms identified by covariate matching based on year, industry

(4-digit code for manufacturing and 2-digit code for others), and asset size. t-values are reported

in the parenthesis, and are based on standard errors clustered at the firm level.

The results on marginal contribution to group control are very similar to those on earnings.


statistically significant when using related-party sales (column 2), positive and marginally

significant when using related-party transactions (sum of related-party sales and purchases), but

not significant when using related-party purchases (column 3). Again, it is related-party sales, not

related-party purchases, that benefit treatment group firms in terms of control over other firms.

This is also consistent with the anecdotal evidence reported by NGOs and popular press.

F. Falsification Tests

Table 8 reports the results of our first falsification test. We run difference-in-differences

regressions identical to those reported in Table 4, but using treatment group firms where ‘non-

heirs’ become a major shareholder. Columns (1) – (3) ((4) – (6)) use 25 (30) treatment group

firms that experienced major increase in controlling shareholder’s (other relative’s) ownership

and 25 (30) control group firms identified by covariate matching based on year, industry (4-digit

code for manufacturing and 2-digit code for others), and asset size. If increase in related-party

transactions are for the benefit of heirs and their successions, it should not respond to changes in

‘non-heir’s’ ownership. This is what we find. The coefficients of our interest (the coefficients on

TGi x TPit) are all positive, but statistically insignificant, indicating that related-party transactions

do not increase in firms where ‘non-heirs’ become a major shareholder.

In our second falsification test, we run difference-in-differences regressions identical to those

reported in Tables 5-7, but using counterparties of the original treatment group firms (e.g. firms

- 19 -

where heir become a major shareholder) as our new treatment group. Again, if increase in related-

party transactions are for the benefit of heirs and their successions, one should not see firms in

the other side of transaction producing higher earnings or strengthening control over other firms.

For this second falsification test, we make use of TS2000, the financial database administered

by Korea Listed Companies Association (KLCA), which provides the name, but not the code of

counterparties (including privately-traded firms) that engage in related-party transactions with

listed firms. Among these counterparties, we exclude individuals and overseas subsidiaries. The

remaining firms become our new treatment group firms. For each treatment group firm, we again

identify matching firms based on year, industry, and asset size. But, we do this only during 2000-

2004, where we have identified the code of counterparties. We plan to extend the sample period

so that it covers that of our key regressions. Presently, we have only 18 firms in our treatment

group.

Table 9 reports the results. iTG takes a value of 1 if firm i is the counterparty of the original

treatment group firm, and 0 otherwise. itTP takes a value of 1 if the original treatment group firm

of firm i experiences a major increase in heir’s net ownership at year t or before. All related-party

transaction variables are defined from the perspective of the counterparty firm. The coefficients

of our interest (the coefficients on TGi x TPit x RPTit) are all statistically insignificant, indicating

that related-party transactions do not improve the counterparty firms’ earnings, dividend payouts,

or strengthen their control over other firms.

5. Conclusion

In this paper, we investigate if families controlling business groups make use of related-party

transactions to benefit firms, in which heirs hold significant equity stakes, and thereby let such

firms grow large enough to strengthen their control over other firms within the group. Using a

sample of Korean chaebol firms during 2000-2009, we report a number of results consistent with

our hypotheses. First, related-party transactions increase in firms where heirs become a major

shareholder (treatment group) after the ownership change (treatment). Second, earnings increase

with related-party transactions in treatment group firms after the treatment. Third, dividend

- 20 -

payout increase with related-party transactions in treatment group firms after the treatment.

Fourth, importance in group control increases with related-party transactions in treatment group

firms after the treatment.

These academic findings confirm the non-academic allegations made by non-governmental

organizations (NGOs) and popular press in Korea. It also justifies the new regulatory actions

taken by the Korean government in recent years to curb tunneling. In December 2011, the

National Assembly passed a bill revising the Inheritance and Gift Tax Act and allowing the

National Tax Office to levy gift tax on expropriated income from related party sales. More

specifically, shareholders individually owning more than 3% (directly or indirectly) of total

outstanding shares of a company, where related-party sales take up more than 30% of its total

sales, are subject to a gift tax. The taxable gift income is equal to earnings before tax (NOPLAT)

× (percentage of related-party sales out of total sales – 15%) × (percentage of shareholding – 3%).

Another regulatory action took place in August 2013. The National Assembly passed a bill

revising the Monopoly Regulation and Fair Trade Act and allowing the Fair Trade Commission

to levy penalty on related-party transactions favoring controlling family members. The new rule

applies to members of large business groups designated by KFTC. To be identified as a

beneficiary firm, controlling family members in aggregate must directly own more than 30

percent of outstanding shares and must have entered related-party transactions in significantly

favorable terms.

We believe our findings are relevant not only to Korea, but also to many other countries.

Family controlled business groups are prevalent in emerging markets and even in some

developed economies (Khanna and Yafeh, 2007). Families controlling these business groups may

use related-party transactions as means of family ownership succession if the country’s

regulatory environment does not permit an easy solution to it.

This paper contributes to the literature in three main ways. First, to the best of our knowledge,

this is the first paper on ‘family ownership’ succession, which we believe is an issue of

paramount importance for family firms, but its research virtually missing in the existing literature.

As mentioned earlier, the main focus of existing papers is on ‘managerial’ succession. Second, we

contribute to the studies on family firm performance, which became popular during the past

several years. We contribute to this area of study by highlighting the importance of related-party

- 21 -

transactions when assessing firm performance, especially when firms are parts of a business

group. Third, we add to the literature on tunneling among business group firms. We report

empirical evidence that related-party transactions can be used as a tunneling vehicle benefiting

founding family members at the expense of outside minority shareholders. Our evidence on

tunneling, however, is indirect in nature like in any other tunneling papers.

- 22 -

References

Almeida, Heitor, Sang Yong Park, Marti Subrahmanyam, and Daniel Wolfenzon (2011), “The Structure and Formation of Business Groups: Evidence from Korean Chaebols,” Journal of Financial Economics, Vol.99, No.2, pp.447-475

Anderson, Ronald and David Reeb (2003), “Founding-Family Ownership and Firm Performance: Evidence from the S&P 500,” The Journal of Finance, Vol.58, pp.1301-1327

Andres, Christian (2008), “Large Shareholders and Firm Performance – An Empirical Examination of

Founding-Family Ownership,” Journal of Corporate Finance, Vol.14, pp.431-445

Bae, Kee-Hong, Jun-Koo Kang, and Jin-Mo Kim (2002), “Tunneling or Value Added? Evidence from Mergers by Korean Business Groups,” The Journal of Finance, Vol.57 No.6, pp.2695-2740

Baek, Jae-Seung, Jun-Koo Kang, and Inmoo Lee (2006), “Business Groups and Tunneling: Evidence from Private Securities Offerings by Korean Chaebols,” The Journal of Finance, Vol.61 No.5, pp.2415-2449

Bennedsen, Morten, Kasper Nielsen, Francisco Perez-Gonzales, and Daniel Wolfenzon (2007), “Inside the Family Firm: The Role of Families in Succession Decisions and Performance,” Quarterly Journal of Economics, Vol.122 No.2, pp.647-691

Bertrand, Marianne, Paras Mehta, and Sendhil Mullainathan (2002), “Ferreting Out Tunneling: An Application to Indian Business Groups,” Quarterly Journal of Economics, Vol.117, pp.121-148

Cheung, Yan-Leung, Raghavendra Rau, and Aris Stouraitis (2006), “Tunneling, Propping, and Expropriation: Evidence from Connected Party Transactions in Hong Kong,” Journal of Financial Economics, Vol.82 No.2, pp.343-386

Claessens, Stijn, Simeon Djankov, and Larry Lang (2000), “The Separation of Ownership and Control in East Asian Corporations,” Journal of Financial Economics, Vol.58, pp.81-112

Cucculelli, Marco and Giancinto Micucci (2008), “Family Succession and Firm Performance: Evidence

from Italian Family Firms,” Journal of Corporate Finance, Vol.14, pp.17-31

Economic Reform Research Institute (2012), “Family Ownership Succession of Chaebol Groups,”

Economic Reform Report No. 2012-17 (in Korean)

Faccio, Mara and Larry H.P. Lang (2002), “The Ultimate Ownership of Western European Corporations,” Journal of Financial Economics Vol.65, pp. 365-395

Gompers, Paul., Joy Ishii, and Andrew Metrick (2010), “Extreme Governance: An Analysis of Dual-Class Firms in the United States, Review of Financial Studies, Vol.23 No.3, pp.1051-1088.

Khanna, Tarun and Yishay Yafeh (2007), “Business Groups in Emerging Markets: Paragons or Parasites?”

Journal of Economic Literature, Vol.45 No2., pp.331-371

- 23 -

Kim, Woochan, Youngjae Lim, and Taeyoon Sung (2007), “Group Control Motive as a Determinant of Ownership Structure in Business Conglomerates: Evidence from Korea’s Chaebols,” Pacific-Basin Finance Journal, Vol.15 No.3, pp.213-252

Lopez de Silanes, Rafael La Porta, and Andrei Shleifer (1999), “Corporate Ownership around the World,”

The Journal of Finance Vol.54 No.2 pp.471-517

Maury, Benjamin (2006), “Family Ownership and Firm Performance: Empirical Evidence from Western

European Corporations,” Journal of Corporate Finance, Vol.12, pp.321-341

McConaughy, Daniel, Michael Walker, Glenn Henderson, and Chandra Mishra (1998), “Founding Family

Controlled Firms: Efficiency and Value, Review of Financial Economics, Vol.7, No.1, pp.1-19

Miller, Danny, Isabelle Le Breton-Miller, Richard Lester, and Albert Cannella (2007), “Are Family Firms

Really Superior Performers?” Journal of Corporate Finance, Vol.13, pp.829-858

Morck, Randall, Andrei Shleifer, and Robert Vishny (1988), “Management Ownership and Market Valuation: An Empirical Analysis,” Journal of Financial Economics, Vol.20, pp.293-315

Nenova, Tatiana (2003), “The Value of Corporate Voting Rights and Control: A Cross-Country Analysis,” Journal of Financial Economics, Vol.68, pp.325-351

Smith, Brian and Ben Amoako-Adu (1999), “Management Succession and Financial Performance of

Family Controlled Firms,” Journal of Corporate Finance, Vol.5, pp.341-368

Villalonga, Belen and Raphael Amit (2006), “How Do Family Ownership, Control, and Management Affect Firm Value?” Journal of Financial Economics, Vol.80, No.2, pp.385-417

Villalonga, Belen and Rephael Amit (2009), “How are U.S. Family Firms Controlled?” Review of

Financial Studies, Vol. 22, No.8, pp.3047-3091

Fig

Following

related-pa

gure 1: Hanw

g figure depic

arty sales volu

wha S&C’s U

cts how major

ume, earnings,

Use of Relat

r change in H

and control o

- 24 -

ted-Party Tr

Hanwha S&C

ver other mem

ransactions f

’s ownership

mber firms in t

for Tunnelin

structure pro

the group.

ng and Succe

mpted the inc

ession

crease in its

25

Table 1: Sample Chaebol Groups

List of chaebol groups, and the number of their member firms in each year. Column (1) lists a total of 26 Chaebols designated by the FTC for at least 6 years during the

sample period of 2000-2009 (e.g. designated in the Aprils of 2001 to 2010). Column (2) counts the number of member firms in each group in each year. Column (3) shows

the controlling shareholders’ names and column (4) the generations from founders (1, 2, and 3 indicates 1st , 2nd, and 3rd generation).

No

(1) (2) (3) (4)

Chaebol Name Number of Member Firms

Controlling Shareholder Gener-

ation 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

1 CJ 26 24 30 38 45 53 60 62 61 53 Lee Jae-Hyun 3

2 Daelim 14 13 13 11 11 12 14 14 16 16 Lee Joon-Yong 2

3 Dongbu 13 15 17 16 14 15 15 21 24 22 Kim Jun-Ki 1

4 Dongkuk Steel 8 6 7 8 8 12 11 12 13 11 Jang Se-Joo 3

5 Doosan 16 16 20 20 17 17 17 19 22 25 Park Yong-Gon 3

6 GS - - - - 40 49 48 57 63 68 Huh Chang-Soo 3

7 Hanjin 17 19 21 21 22 21 25 27 32 37 Cho Joong-Hoon (~2002), Cho Yang-Ho (2003~) 1, 2

8 Hanwha 21 22 27 25 25 24 27 33 35 40 Kim Seung-Youn 2

9 Hyosung 14 14 14 15 15 16 22 28 39 38 Cho Suk-Rae 2

10 Hyundai 18 11 9 8 6 9 8 8 9 11 Chung Mong-Hun (~2003), Hyun Jeong-Eun (2004~) 2, 3

11 Hyundai Department Store 15 10 19 17 20 23 24 25 24 29 Chung Mong-Keun (~2006), Chung Ji-Sun (2007~) 2, 3

12 Hyundai Development Company 8 9 10 11 11 12 15 14 15 14 Chung Se-Young (~2006), Chung Mong-Kyu (2007~) 1, 2

13 Hyundai Heavy Industries - - 3 3 4 4 4 6 8 10 Chung Mong-Joon 2

14 Hyundai Motor Company 14 21 21 26 26 37 34 33 37 38 Chung Mong-Koo 2

15 KCC - 5 5 6 4 4 4 6 9 9 Chung Sang-Yong 1

16 Kolon 22 28 31 30 27 22 33 33 37 35 Lee Dong-Chan (~2006), Lee Woong-Yeol (2007~) 2, 3

17 Kumho 14 13 13 14 16 21 34 50 47 46 Park Sung-Yong (~2005), Park Sam-Koo (2006~) 2, 2

18 LG 37 46 45 45 47 32 31 36 52 53 Koo Bon-Moo 3

19 Lotte 30 31 33 33 39 41 42 43 51 57 Shin Kyuk-Ho 1

20 LS - - - 7 17 19 19 23 31 43 Koo Tae-Hoi 1

21 OCI 22 19 19 19 18 19 18 15 18 18 Lee Hoi-Rim (~2007), Lee Soo-Young (2008~) 1, 2

22 Samsung 55 54 54 55 53 49 50 49 53 57 Lee Kun-Hee 2

23 Shinsegae 9 10 12 12 13 14 15 15 15 12 Lee Myung-Hee 2

24 SK 50 57 55 54 46 54 55 63 75 74 Chey Tae-Won 2

25 Tongyang 20 8 7 8 8 8 14 13 15 17 Hyun Jae-Hyun 2

26 Youngpoong 23 24 23 20 19 26 22 21 22 23 Jang Byung-Hee (~2002), Jang Hyung-Jin (2003~) 1, 2

Total number of Chaebols 22 23 24 25 26 26 26 26 26 26

Total number of group firms 466 475 508 522 571 613 661 726 823 856

26

Table 2: Variable Definitions and Summary Statistics

Definition and summary statistics of variables used in this paper. Panel A defines each variable. Panel B

provides summary statistics for each family group. We use nonfinancial firms from 26 chaebol groups (see Table

1) during 2000-2009.

Panel A. Variable Definitions

Variables Definitions

Left-Hand Side Variables

RPTit ln[(sum of related-party sales and purchases/ GDP deflator) + 1]; related-party

sales and purchase are measured in million Korean won (approximately

thousand US dollars)

RPSit ln[(related-party sales/ GDP deflator) + 1]; related-party sales are measured in

million Korean won (approximately thousand US dollars)

RPPit ln[(related-party purchases/ GDP deflator) + 1]; related-party purchase are

measured in million Korean won (approximately thousand US dollars)

EBITDAit ln(absolute value of earnings before interest, taxes, depreciation and

amortization/GDP deflator) x sign of original EBITDA if its absolute value is

greater than 1, and 0 otherwise.

MCIit Marginal contribution to group control index; winsorized at the 99th percentile

values; see Section 3.C for the details of its definition.

DIVit ln[(dividend/ GDP deflator) + 1]; dividend is measured in million Korean won

(approximately thousand US dollars)

Right-Hand Side Variables

TGi Treatment group dummy, which takes a value of 1 if the firm i experiences a

major increase in heir’s ownership and 0 otherwise. Major increase in heir’s

ownership means that its net ownership (heir’s ownership – controlling

shareholder’s ownership – other relatives’ ownership) increases by more than

5%p and it is greater than both, the controlling shareholder’s ownership and

the other relatives’ ownership. Other treatment group dummies used in our

falsification tests are similarly defined.

TPit Treatment period dummy that takes a value of 1 if firm i is treated at year t or

before. Notice that this treatment period dummy is defined separately for each

treatment group firm i. Firm i and firm i’s matching firm takes the same value

for TPit.

NOWN_Hit Heir’s net ownership; heir’s ownership (OWN_Hit) – controlling shareholders’

ownership (OWN_Cit) – other relatives’ ownership (OWN_Rit)

NOWN_Cit Controlling shareholders’ net ownership; controlling shareholders’ ownership

(OWN_Cit) – heir’s ownership (OWN_Hit) – other relatives’ ownership

(OWN_Rit)

NOWN_Rit Other relatives’ net ownership; other relatives’ ownership (OWN_Rit) – heir’s

ownership (OWN_Hit) – controlling shareholders’ ownership (OWN_Cit)

Firm size ln(Total assets/GDP deflator); total assets are measured in million Korean

won (approximately thousand US dollars)

Firm age Number of years since a firm’s establishment, measured by ln(year - year of

establishment)

Leverage ln[(Book value of debt /total assets)+1]

Cash holdings ln(Cash and cash equivalents / total assets)

R&D expenditure ln[(R&D/ Sales) x 100 +1]; winsorized at the 99th percentile values

Advertising expenditure ln[(Advertising / Sales) x 100 +1]; winsorized at the 99th percentile values

Spin-off 1 if a firm experiences spin-off at year t or before, and 0 otherwise.

Merger 1 if a firm experiences merger at year t or before, and 0 otherwise.

New affiliate 1 if a firm is affiliated to a business group at year t or before, and 0 otherwise.

27

Panel B. Summary Statistics

Variables Heir Controlling Shareholders Other Relatives

N Mean Med. S.D. Min. Max. N Mean Med. S.D. Min. Max. N Mean Med. S.D. Min. Max.

RPTit 632 10.85 10.95 1.95 0.00 15.47 416 10.66 10.75 2.19 0.00 14.67 507 9.64 9.74 2.86 0.00 14.93

RPSit 632 10.02 10.36 2.56 0.00 15.18 416 9.32 10.14 3.12 0.00 14.29 507 8.49 9.29 3.45 0.00 14.06

RPPit 632 8.98 9.32 2.72 0.00 14.70 416 9.09 9.54 3.13 0.00 14.03 507 7.87 8.19 3.64 0.00 14.68

EBITDAit 617 7.26 9.00 5.85 -11.49 14.42 384 8.17 9.25 5.31 -13.16 13.94 495 6.27 8.37 6.34 -13.16 13.64

MCIit 626 0.26 0.00 0.72 0.00 3.98 418 0.23 0.00 0.65 0.00 3.98 459 0.28 0.00 0.59 0.00 3.98

DIVit 616 3.93 0.00 4.17 0.00 12.38 384 4.14 0.00 4.38 0.00 11.58 495 2.75 0.00 3.89 0.00 11.58

TGi 650 0.51 1.00 0.50 0.00 1.00 430 0.53 1.00 0.50 0.00 1.00 538 0.50 0.50 0.50 0.00 1.00

TPit 650 0.49 0.00 0.50 0.00 1.00 430 0.50 1.00 0.50 0.00 1.00 538 0.54 1.00 0.50 0.00 1.00

NOWNit 637 0.02 0.00 0.19 -0.60 1.00 430 -0.03 0.00 0.09 -0.44 0.20 482 -0.11 0.00 0.33 -1.00 0.75

OWNit 637 0.07 0.00 0.15 -0.03 1.00 430 0.03 0.00 0.07 -0.01 0.43 482 0.13 0.00 0.29 -0.41 1.00

Firm size 617 11.99 12.01 1.52 8.66 15.86 384 12.32 12.18 2.10 6.45 17.03 495 11.68 11.16 1.88 8.26 15.95

Firm age 629 2.45 2.64 0.96 0.00 4.09 415 2.48 2.64 1.08 0.00 4.03 516 2.32 2.30 1.08 0.00 4.33

Leverage 617 0.43 0.44 0.13 0.01 0.72 384 0.43 0.46 0.15 0.01 0.76 495 0.47 0.49 0.17 0.00 1.16

Cash holdings 617 0.06 0.04 0.07 0.00 0.51 384 0.06 0.03 0.09 0.00 0.64 495 0.06 0.02 0.09 0.00 0.51

R&D 650 0.08 0.00 0.27 0.00 1.42 430 0.12 0.00 0.32 0.00 1.42 538 0.05 0.00 0.20 0.00 1.42

Advertising 650 0.30 0.04 0.57 0.00 2.88 430 0.23 0.04 0.39 0.00 2.56 538 0.35 0.06 0.51 0.00 2.88

Spin-off 650 0.00 0.00 0.00 0.00 0.00 430 0.00 0.00 0.00 0.00 0.00 538 0.00 0.00 0.04 0.00 1.00

Merger 650 0.00 0.00 0.00 0.00 0.00 430 0.01 0.00 0.12 0.00 1.00 538 0.00 0.00 0.00 0.00 0.00

New Affiliate 650 0.00 0.00 0.00 0.00 0.00 430 0.00 0.00 0.00 0.00 0.00 538 0.02 0.00 0.14 0.00 1.00

28

Table 3: Changes in RPT and EBITDA Before and After Ownership Changes

The median (Panel A) and the mean (Panel B) of paired-sample differences in RPTit, RPSit, RPPit, and EBITDAit

before and after net ownership change of various degrees (±5%p, ±10%p, and ±15%p) for each family group

(heir, controlling shareholder, and other relatives). See Table 2 for the definitions of RPTit, RPSit, RPPit, and

EBITDAit. The year of net ownership change is not used in the computation. Sample consists of nonfinancial

firms from 26 chaebol groups (see Table 1) during 2000-2009. We exclude firms that underwent a spin-off or a

merger from the sample. We also exclude newly added member firms during the sample period.

Panel A: Median of paired-sample differences

△Ownership Before △Ownership - After △Ownership no. of years

(before)

no. of

years

(after)

no. of

firmsRPTit RPSit RPPit EBITDAit DIVit

NOWN_Hit

> 15%p 1.38 1.13 1.67 1.11 0.14 3.7 3.8 22

> 10%p 1.11 0.88 1.60 0.98 0.00 3.6 3.7 27

> 5%p 0.64 0.87 0.80 0.63 0.00 3.5 3.8 35

< -5%p 0.32 0.16 0.09 0.30 0.72 3.6 3.3 37

< -10%p 0.41 0.10 0.21 0.38 0.12 3.4 3.7 24

< -15%p 0.64 0.20 0.51 0.46 0.11 3.0 3.1 16

NOWN_Cit

> 15%p 0.92 0.58 2.70 0.55 0.36 5.5 3.0 4

> 10%p 0.41 0.28 0.22 0.30 0.49 4.6 3.1 10

> 5%p 0.48 0.66 0.23 0.31 0.99 4.6 3.1 17

< -5%p 0.59 0.35 0.59 0.29 0.11 3.9 3.4 49

< -10%p 0.90 0.39 0.76 0.36 0.14 4.1 3.0 35

< -15%p 1.24 0.40 0.91 0.63 0.27 4.2 3.1 26

NOWN_Rit

> 15%p 0.66 0.39 0.44 0.62 0.31 3.8 2.7 13

> 10%p 0.66 0.39 0.44 0.62 0.31 3.9 3.2 13

> 5%p 0.26 0.16 0.65 0.19 1.35 3.8 3.1 18

< -5%p 0.61 0.68 0.49 0.47 0.09 3.5 4.0 42

< -10%p 0.77 0.32 0.56 0.58 0.13 3.2 4.4 28

< -15%p 1.22 0.95 0.80 0.84 0.05 3.3 4.1 21

Panel B: Mean of paired-sample differences

△Ownership Before △Ownership - After △Ownership no. of years

(before)

no. of

years

(after)

no. of

firmsRPTit RPSit RPPit EBITDAit DIVit

NOWN_Hit

> 15%p 2.73 2.33 3.25 3.85 1.34 3.7 3.8 22

> 10%p 2.17 1.85 2.99 3.28 0.83 3.6 3.7 27

> 5%p 1.64 1.57 2.20 2.41 0.35 3.5 3.8 35

< -5%p 0.84 0.29 0.55 0.85 1.23 3.6 3.3 37

< -10%p 1.05 0.25 0.64 1.15 0.70 3.4 3.7 24

< -15%p 1.64 0.36 1.36 1.37 0.49 3.0 3.1 16

NOWN_Cit

> 15%p 0.85 0.90 1.53 2.09 0.88 5.5 3.0 4

> 10%p 0.60 0.66 0.95 0.12 1.33 4.6 3.1 10

> 5%p 0.68 1.06 0.88 1.88 1.83 4.6 3.1 17

< -5%p 1.13 0.43 1.09 1.24 0.09 3.9 3.4 49

< -10%p 1.56 0.56 1.53 1.73 -0.01 4.1 3.0 35

< -15%p 1.99 0.56 1.84 2.56 0.87 4.2 3.1 26

NOWN_Rit

> 15%p 1.83 1.63 1.39 1.92 2.12 3.8 2.7 13

> 10%p 1.65 1.49 1.19 1.82 1.99 3.9 3.2 13

> 5%p 1.27 1.06 1.34 1.57 2.60 3.8 3.1 18

< -5%p 0.84 0.66 0.96 1.40 1.07 3.5 4.0 42

< -10%p 0.79 0.39 0.81 1.32 1.54 3.2 4.4 28

< -15%p 1.02 0.56 1.01 2.69 1.24 3.3 4.1 21

29

Table 4: Ownership Change and Related-Party Transactions

Firm fixed effects regressions of related-party transactions (RPTit, RPSit, and RPPit) on treatment group dummy

(TGi), treatment period dummy (TPit), their interaction (TGi x TPit), control variables, and year dummies. We

also include time-varying dummies capturing spin-offs, mergers, and new affiliates, but their coefficients are

suppressed. Treatment group dummy (TGi) is absorbed in firm FE. Sample include 36 treatment group firms that

experienced major increase in heir’s ownership and 36 control group firms identified by covariate matching

based on year, industry (4-digit code for manufacturing and 2-digit code for others), and asset size. t-values are

reported in the parenthesis, and are based on standard errors clustered at the firm level. *, **, and ***

respectively indicate significance at 10%, 5%, and 1% levels. Significant results (at 10% level or better) are

shown in boldface.

(1) (2) (3)

Related-party

Transactions (RPTit)

Related-party

Sales (RPSit)

Related-party

Purchases (RPPit)

TPit -0.1324 -0.2667 -0.2387

(-0.93) (-1.38) (-0.92)

TGi x TPit 0.3906* 0.6021* 0.6158*

(1.80) (1.67) (1.75)

Firm size 0.6822*** 0.3782 1.0067*** (3.23) (1.50) (3.48)

Firm age 0.3279* 0.6744* 0.2891

(1.72) (1.84) (0.76)

Leverage -0.3840 0.2795 -0.6671

(-0.34) (0.23) (-0.39)

Constant Yes Yes Yes

Firm FE Yes Yes Yes

Year FE Yes Yes Yes

Observations 602 602 602

Number of firms 72 72 72

within R-sq 0.192 0.136 0.167

30

Table 5: Ownership Change, Related-Party Transactions, and Earnings

Firm fixed effects regressions of earnings (EBITDAit) on treatment group dummy (TGi), treatment period

dummy (TPit), related-party transactions (RPTit, RPSit, or RPPit), their interactions, control variables, and year

dummies. Treatment group dummy (TGi) is absorbed in firm FE. Sample include 36 treatment group firms that





shown in boldface.

(1) (2) (3)

Dependent Var. EBITDAit

Types of RPT Related-Party


Related-party

Sales (RPSit)

Related-party

Purchases (RPPit)

TPit 6.6177* 6.1879*** 4.3488*

(1.84) (2.79) (1.75)

RPTit 0.7819 0.6752*** 0.5615*

(1.64) (3.31) (1.99)

TGi x TPit -9.8245* -8.4469** -4.1508

(-1.89) (-2.51) (-1.52)

TGi x RPTit -0.2157 -0.3760 -0.2650

(-0.34) (-1.14) (-0.76)

TPit x RPTit -0.5789* -0.5740** -0.4506*

(-1.78) (-2.60) (-1.85)

TGi x TPit x RPTit 0.7650* 0.6947** 0.3094

(1.71) (2.15) (1.11)

Firm size 0.5215 0.9003 0.4839

(0.70) (1.29) (0.64)

Firm age 2.6736*** 2.5072*** 2.6968*** (3.12) (3.07) (2.95)

Leverage -5.3704 -6.0444 -5.3130

(-1.38) (-1.64) (-1.42)

Cash holdings 2.8052 2.7519 4.6822

(0.60) (0.61) (0.94)

R&D expenditure -0.4417 -0.5094 -0.3162

(-0.39) (-0.49) (-0.30)

Advertising expenditure -2.3931** -2.5513** -2.2672**

(-2.12) (-2.12) (-2.33)


Firm FE Yes Yes Yes

Year FE Yes Yes Yes



within R-sq 0.102 0.112 0.0956

31

Table 6: Ownership Change, Related-Party Transactions, and Dividends

Firm fixed effects regressions of dividends (DIVit) on treatment group dummy (TGi), treatment period dummy

(TPit), related-party transactions (RPTit, RPSit, or RPPit), their interactions, control variables, and year dummies.

Treatment group dummy (TGi) is absorbed in firm FE. Sample include 36 treatment group firms that





shown in boldface.

(1) (2) (3)

Dependent Var. DIVit



Related-party

Sales (RPSit)

Related-party

Purchases (RPPit)

TPit 0.4972 1.5026 0.0104

(0.33) (1.37) (0.01)

RPTit 0.1426 0.1693* 0.0893

(0.74) (1.84) (0.74)

TGi x TPit -2.2009 -3.7044*** -0.7998

(-1.14) (-2.72) (-0.48)

TGi x RPTit 0.1695 -0.0175 0.0007

(0.63) (-0.11) (0.00)

TPit x RPTit -0.0276 -0.1271 0.0144

(-0.21) (-1.33) (0.09)

TGi x TPit x RPTit 0.0811 0.2402* -0.0413

(0.47) (1.87) (-0.24)

Firm size 0.3718 0.4890 0.4414

(1.17) (1.52) (1.34)

Firm age 1.0798** 1.0415** 1.0873** (2.20) (2.20) (2.18)

Leverage -3.5381** -3.6166** -3.4048** (-2.11) (-2.23) (-2.03)


Firm FE Yes Yes Yes

Year FE Yes Yes Yes



within R-sq 0.124 0.127 0.117

32

Table 7: Ownership Change, Related-Party Transactions, and Group Control

Firm fixed effects regressions of marginal contribution to group control index (MCIit) on treatment group

dummy (TGi), treatment period dummy (TPit), related-party transactions (RPTit, RPSit, or RPPit), their

interactions, and year dummies. Treatment group dummy (TGi) is absorbed in firm FE. Sample include 36

treatment group firms that experienced major increase in heir’s ownership and 36 control group firms identified

by covariate matching based on year, industry (4-digit code for manufacturing and 2-digit code for others), and

asset size. t-values are reported in the parenthesis, and are based on standard errors clustered at the firm level. *,

**, and *** respectively indicate significance at 10%, 5%, and 1% levels. Significant results (at 10% level or

better) are shown in boldface.

(1) (2) (3)

Dependent Var. MCIit



Related-party

Sales (RPSit)

Related-party

Purchases (RPPit)

TPit 0.1457 0.1285 0.0577

(1.10) (1.29) (0.49)

RPTit 0.0013 0.0006 0.0019

(0.19) (0.15) (0.36)

TGi x TPit -0.4203 -0.4640* -0.0036

(-1.24) (-1.93) (-0.02)

TGi x RPTit -0.0132 -0.0259 0.0140

(-0.58) (-1.47) (0.60)

TPit x RPTit -0.0127 -0.0121 -0.0049

(-1.06) (-1.35) (-0.38)

TGi x TPit x RPTit 0.0564* 0.0663** 0.0199

(1.67) (2.23) (1.02)


Firm FE Yes Yes Yes

Year FE Yes Yes Yes



within R-sq 0.0972 0.113 0.0975

33

Table 8: Falsification Tests on Related-Party Transactions

Firm fixed effects regressions, identical to those reported in Table 4, but using treatment group dummy (TGi),

where non-heirs (controlling shareholder or other relatives) become a major shareholder. Columns (1) – (3) ((4)

– (6)) use 25 (30) treatment group firms that experienced major increase in controlling shareholder’s (other

relative’s) ownership and 25 (30) control group firms identified by covariate matching based on year, industry

(4-digit code for manufacturing and 2-digit code for others), and asset size. t-values are reported in the

parenthesis, and are based on standard errors clustered at the firm level. *, **, and *** respectively indicate

significance at 10%, 5%, and 1% levels. Significant results (at 10% level or better) are shown in boldface.

(1) (2) (3) (4) (5) (6)

Dependent

Variable

Related-party

Transactions

(RPTit)

Related-party

Sales

(RPSit)

Related-party

Purchases

(RPPit)

Related-party

Transactions

(RPTit)

Related-party

Sales

(RPSit)

Related-party

Purchases

(RPPit)

Treatment Group Controlling Shareholder Other Relatives

TPit -0.0445 -0.2236 -0.3127 0.0841 0.3954 -0.1440

(-0.26) (-0.69) (-1.08) (0.46) (1.63) (-0.27)

TGi x TPit 0.2476 0.4820 0.0168 0.8179 0.5802 0.4540

(0.75) (0.85) (0.04) (1.50) (1.23) (0.58)

Firm size 0.5519*** 0.1893 1.0197** 0.5978 0.3947 0.7913

(3.86) (0.76) (2.49) (1.33) (1.04) (1.28)

Firm age 0.6401*** 0.9985* 1.1190* 0.2937 0.9491** -0.5816

(2.69) (1.88) (1.71) (1.08) (2.31) (-0.98)

Leverage 0.0671 -0.9718 3.1549* 3.1539 3.5072 4.6526**

(0.09) (-0.86) (1.93) (1.66) (1.42) (2.41)

Constant Yes Yes Yes Yes Yes Yes

Firm FE Yes Yes Yes Yes Yes Yes

Year FE Yes Yes Yes Yes Yes Yes

Observations 379 379 379 473 473 473

Number of firms 50 50 50 60 60 60

within R-sq 0.186 0.135 0.201 0.408 0.249 0.293

34

Table 9: Falsification Tests on Earnings, Dividends, and Group Control

Firm fixed effects regressions, identical to those reported in Tables 5, 6, and 7, but using counterparties of the original treatment group firms (e.g. firms where heir become

a major shareholder) as our new treatment group. TGi takes a value of 1 if firm is the counterparty of the original treatment group firm, and 0 otherwise. TPit takes a value

of 1 if the original treatment group firm of firm experiences a major increase in heir’s net ownership at year t or before. Control variables are suppressed. We use 18

treatment group firms and 18 control group firms identified by covariate matching based on year, industry (4-digit code for manufacturing and 2-digit code for others), and

asset size. t-values are reported in the parenthesis, and are based on standard errors clustered at the firm level. *, **, and *** respectively indicate significance at 10%, 5%,

and 1% levels. Significant results (at 10% level or better) are shown in boldface.

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Dependent Variables EBITDAit DIVit MCIit

Types of RPT

Related

-party

Transactions

(RPTit)

Related

-party

Sales

(RPSit)

Related

-party

Purchases

(RPPit)

Related

-party

Transactions

(RPTit)

Related

-party

Sales

(RPSit)

Related

-party

Purchases

(RPPit)

Related

-Party

Transactions

(RPTit)

Related

-party

Sales

(RPSit)

Related

-party

Purchases

(RPPit)

TPit 4.8967** 2.7009** 3.4178** 2.6272 0.3328 -0.4909 -0.4464 -0.8437 -0.2535

(2.81) (2.31) (2.57) (0.65) (0.11) (-0.15) (-0.29) (-1.23) (-0.25)

RPTit -0.3113 0.0589 0.0333 -0.5571 0.0083 0.0112 -0.0032 0.0226 -0.0586

(-1.63) (0.55) (0.19) (-0.98) (0.03) (0.04) (-0.02) (0.36) (-0.47)

TGi x TPit 0.0891 3.1138 0.3096 -3.9350 0.4450 -2.0819 1.0402 1.3039 0.6710

(0.05) (1.19) (0.19) (-0.69) (0.07) (-0.49) (0.63) (1.52) (0.59)

TGi x RPTit 0.8316* 0.5450 0.4239 1.5417 1.0397 0.5971 -0.0397 -0.0567 0.0506

(1.83) (1.00) (1.31) (1.69) (1.08) (0.91) (-0.23) (-0.76) (0.38)

TPit x RPTit -0.3770** -0.2166** -0.2742** -0.2147 0.0016 0.0510 0.0335 0.0698 0.0180

(-2.75) (-2.32) (-2.57) (-0.74) (0.01) (0.21) (0.28) (1.17) (0.22)

TGi x TPit x RPTit 0.0175 -0.2203 -0.0084 0.5099 0.1869 0.3533 -0.0731 -0.1020 -0.0479

(0.13) (-1.17) (-0.07) (1.15) (0.37) (0.96) (-0.55) (-1.42) (-0.51)

Constant Yes Yes Yes Yes Yes Yes Yes Yes Yes

Control Variables Yes Yes Yes Yes Yes Yes Yes Yes Yes

Firm FE Yes Yes Yes Yes Yes Yes Yes Yes Yes

Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes

Observations 170 170 170 170 170 170 169 169 169

Number of firms 18 18 18 18 18 18 18 18 18

within R-sq 0.566 0.562 0.560 0.400 0.371 0.380 0.0672 0.135 0.0654

i

i

when heirs become major shareholders 20140606 - uni … · 2019. 9. 29. · munich personal repec...

Documents